Open Access

ARTICLE

Genetic Algorithm and Tabu Search Memory with Course Sandwiching (GATS_CS) for University Examination Timetabling

Abayomi-Alli A.¹, Misra S.^2,3, Fernández-Sanz L.⁴, Abayomi-Alli O.^2,*, Edun A. R.¹

1 Department of Computer Science, Federal University of Agriculture, Abeokuta, Nigeria.
2 Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria.
3 Department of Computer Engineering, Atilim University, Ankara, Turkey.
4 Department of Computer Science, University of Alcalá, Spain.

* Corresponding Author: Abayomi-Alli Adebayo,

Intelligent Automation & Soft Computing 2020, 26(3), 385-396. https://doi.org/10.32604/iasc.2020.013915

Abstract

University timetable scheduling is a complicated constraint problem because educational institutions use timetables to maximize and optimize scarce resources, such as time and space. In this paper, an examination timetable system using Genetic Algorithm and Tabu Search memory with course sandwiching (GAT_CS), was developed for a large public University. The concept of Genetic Algorithm with Selection and Evaluation was implemented while the memory properties of Tabu Search and course sandwiching replaced Crossover and Mutation. The result showed that GAT_CS had hall allocation accuracies of 96.07% and 99.02%, unallocated score of 3.93% and 0.98% for first and second semesters, respectively. It also automatically sandwiched (scheduled) multiple examinations into single halls with a simulation time in the range of 20-29.5 seconds. The GAT_CS outperformed previous related works on the same timetable dataset. It could, however, be improved to reduce clashes, duplications, multiple examinations and to accommodate more system-defined constraints.

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Citations